Land use and land cover (LULC) changes play a crucial role in regional carbon dynamics and climate regulation. This study assesses the impact of LULC changes on carbon stocks in Hunan Province, China, from 2000 to 2035 using a MOP-PLUS–InVEST–OPGD integrated modeling framework. Results show that carbon stock declined by 45.96 million tons from 2000 to 2020 due to rapid urban expansion and conversion of forest and grassland to construction land. Scenario simulations reveal that by 2035, carbon stock will increase by 4.82% under the ecological protection scenario (EP) but decrease by 3.26% under the natural trend scenario (NT). Economic development scenario (ED) and sustainable development scenario (SD) produce intermediate outcomes. Spatially, high-carbon regions are concentrated in high-altitude forested areas, while urbanized lowlands exhibit the lowest carbon density. The optimal parameters-based geographical detector (OPGD) model identifies land use intensity, elevation, and net primary productivity as the dominant drivers of carbon stock variation, with significant interactions between natural and socioeconomic factors. These findings underscore the need for integrated land-use planning and ecological conservation policies that align with carbon neutrality goals. This study provides a replicable spatial framework and policy-oriented insights for managing carbon stocks in rapidly developing regions.

Hilly mountainous regions are ecologically complex, featuring diverse environmental ecosystem services (ESs) and intricate interactions. However, the variability, drivers, and management of these ESs remain poorly understood, particularly in regions with significant topographical and climatic heterogeneity. This study focuses on the southern hilly mountain belt of China, examining five key ecosystem services: food production (FP), carbon storage (CS), water yield (WY), habitat quality (HQ), and soil conservation (SC). This study examines these ESs across long-term, pixel, and regional scales, exploring the interactive relationships and identifying the driving factors and cluster characteristics. The results indicate the following: (1) Over the past 23 years, although food production and carbon storage have increased, habitat quality has declined. (2) From a spatial perspective, the differences in trade-offs and synergies across the years are relatively small. However, significant differences are observed when considering continuous temporal change, and trade-off relationships are generally prevalent. Additionally, the distribution of trade-offs and synergies is also influenced by a combination of factors. (3) Climatic, vegetation, topographical, and socioeconomic factors are key factors influencing the distribution and changes in ESs. For instance, climate–vegetation interactions enhance carbon storage and soil conservation. Socioeconomic factors, though less impactful, optimize ESs through land management and policy. (4) We found that the ecological priority region covers the largest area, followed by the hilly agricultural development zone, the mountainous agricultural and forestry development zone, and the integrated ecological security zone. These findings deepen our understanding of ESs in hilly mountainous regions, providing actionable insights for enhancing conservation and sustainable management in complex landscapes.